Faculty Publications

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Author: search.filters.author.Swamy, K.B.M.Has files: No

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    Photonic Integrated Piezo-MEMS (Pip-MEMS) Device for 1D Beam Scanning
    (Springer Science and Business Media Deutschland GmbH, 2024) Venkatachalam, P.; Yumnam, D.; Gali, S.; Swamy, K.B.M.; Selvaraja, S.K.
    We demonstrate a 1D beam scanning device with a maximum scan angle of 6.6° at 18.91 kHz for a 0.5 mm long PZT-on-SiN waveguide integrated Piezo-MEMS cantilever. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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    Design and experimental analysis of a non-magnetic cantilever beam in a remotely controlled free vibration setup using LabVIEW
    (American Institute of Physics, 2025) Bidari, L.; Kamath, N.; Kaup, P.S.; Swamy, K.B.M.; Kalluvalappil, G.
    Free vibration analysis finds a plethora of applications in real-world systems, ranging from deciding design factors to addressing maintenance concerns; hence, it forms a fundamental basis of material sciences and structural engineering. Cantilever structures are widespread across various physical systems, from domestic applications such as diving boards or parking shields to heavy-duty industrial applications such as airplane wings or windmill blades. In this paper, a non-magnetic cantilever beam is excited using a cam attached to a stepper motor. The trigger results in free vibrations of the cantilever beam and this data is collected by the accelerometer. The entire experiment is carried out distantly using LabVIEW remote panels, and frequency analysis and calculations are performed on the vibration data collected. The designed remote experimental setup provided near-accurate results for natural frequency calculation, and this is validated experimentally using an impact hammer and theoretically using physical parameters. The remote setup provides the freedom to model and simulate different physical conditions and systems as cantilever structures in the experimental environment. This results in an easy understanding of beam behavior in real-time systems. © 2025 Author(s).
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    Comprehensive simulation study on AlN, ZnO, and PZT-5H piezoelectric materials for microcantilever-based MEMS energy harvesters: Mechanical and electrical insights
    (SAGE Publications Ltd, 2024) Manvi, M.; Swamy, K.B.M.
    The piezoelectric effect involves the generation of electric charge in specific materials when subjected to mechanical stress or strain. This phenomenon is utilized in applications such as sensors, actuators, and energy harvesters. Microelectromechanical systems (MEMS) based piezoelectric energy harvesters are especially useful for powering microelectronic devices and sensors, reducing dependency on batteries in situations where regular battery maintenance and/or replacement is either difficult or impractical. While individual piezoelectric materials like aluminum nitride (AlN), zinc oxide (ZnO) and lead zirconate titanate (PZT) have been extensively studied, comparative analyses within a single context are important for designers, but seldom reported. Accordingly, this article presents a comprehensive study on MEMS energy harvesters, focusing on well-known materials like AlN, ZnO, and PZT-5H. Using finite element method based COMSOL Multiphysics software tool, the proposed energy harvesters are simulated and analyzed for their mechanical and electrical properties to evaluate the performance for typical applications. The resonant frequencies for AlN, ZnO, and PZT-5H harvesters are identified at 3300, 2900, and 2800 Hz, respectively, with corresponding power outputs of about 1.28, 190.5, and 0.004 nW under a “1 g” acceleration. This precise evaluation facilitates designers on informed material selection based on performance metrics, enhancing MEMS energy harvester development. Notably, the significantly higher power output for ZnO compared to AlN and PZT-5H challenges conventional material preferences and offers new possibilities for efficient energy harvesting solutions. © IMechE 2024.
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    Attention-enhanced neural network-based metaheuristic optimization frameworks for enhancing tensile strength in 3D printing
    (SAGE Publications Ltd, 2025) Nejkar, H.; Swamy, K.B.M.
    A comprehensive framework to predict and optimize the tensile strength for fused deposition modeling (FDM) 3D printed polylactic acid specimens is presented in the study. The normalized printing speed, layer thickness, and nozzle temperature are used here in the proposed attention-enhanced neural network (AENN) prediction model, as input variables. A trained attention layer to assign weights per parameter and Monte Carlo dropout to quantify prediction uncertainty are utilized. Incorporating 27 full-factorial experiments, a mean absolute error (MAE) of 0.33?MPa and a maximum relative error (MRE) of 3.43% was achieved for AENN, outperforming the traditional Ridge Regression method (MAE of 2.61?MPa and MRE of 10%). Two metaheuristic optimization algorithms—Firefly algorithm and JAYA algorithm, are used to optimize print speed (39?mm/s), layer thickness (0.30?mm) and nozzle temperature (218°C) for maximum tensile strength. Both algorithms converge on nearly identical settings, with JA demonstrating slightly smoother convergence. Experimental validation with the average tensile strength of 43.52?MPa, confirms the AENN's predictive capability and optimization framework's robustness toward enhancing performance of FDM printed parts. Such frameworks can be adopted for other materials, additional parameters, or multiple objectives. © IMechE 2025